MultiGraphConvolution example

  It simplifies the overall framework, but might be moved to

  GraphEncoderLayer in the future in order to reduce number of layers.

  Example

  --------

  vertices = 9

  nodes = 5

  edges = 5

  units = 128

  layer_1 = MultiGraphConvolutionLayer(units=(128,64))

  layer_2 = GraphAggregationLayer(units=128)

  adjacency_tensor= layers.Input(shape=(vertices, vertices, edges))

  node_tensor = layers.Input(shape=(vertices,nodes))

  hidden = layer_1([adjacency_tensor,node_tensor])

  output = layer_2(hidden)

  model = keras.Model(inputs=[adjacency_tensor,node_tensor], outputs=[output])

  References

  ----------

  .. [1] Nicola De Cao et al. "MolGAN: An implicit generative model